Investigating the concentration of High Yield Investment Programs in the United Kingdom

Ponzi schemes that offer absurdly high rates of return by relying on more and more people paying into the scheme have been documented since at least the mid-1800s. Ponzi schemes have shifted online in the Internet age, and some are re-branded as HYIPs or High Yield Investment Programs. This paper focuses on understanding HYIPs' continuous presence and presents various possible reasons behind their existence in today's world. A look into the countries where these schemes purport to exist, we find that 62.89% of all collected HYIPs claim to be in the United Kingdom (UK), and a further 55.56% are officially registered in the UK as a 'limited company' with a registration number provided by the UK Companies House, a UK agency that registers companies. We investigate other factors influencing these schemes, including the HYIPs' social media platforms and payment processors. The lifetime of the HYIPs helps to understand the success/failure of the investment schemes and helps indicate the schemes that could attract more investors. Using Cox proportional regression analysis, we find that having a valid UK address significantly affects the lifetime of an HYIP

“Invest in crypto!”: An analysis of investment scam advertisements found in Bitcointalk

This paper investigates the evolution of investment scam lures and scam-related keywords in the cryptocurrency online forum Bitcointalk over a period of 12 years. Our findings show a shift in scam-related keywords found within posts in the forum, where “Ponzi” was the most popular and most frequently mentioned in 2014 and 2018 and “HYIP” appeared more often in 2018 and 2021. We also identify that the financial principle is the tactic more likely to be used to lure people into investment scams from 2015 until 2017, coinciding with the period when “Ponzi” was the most commonly found keyword. This is followed by a transition to the authority and distraction principles from 2018 until 2022, which also coincides with the increase of popularity of “HYIP”. We collect more than 17.8M posts from 399k threads from the forum from July 2010 until June 2022. Our longitudinal analysis shows the popularity transition between subforums and keywords across time. We design a categorisation criteria and annotate 4,218 posts from 2,630 threads based on it. We then use the annotated sample to train four machine learning statistical models. We use the best performing model to classify all 281k English-language threads into four categories: overt scams, potential scams, scam comments and not investment scam related. We analyze the frequency changes of scam-related threads across the 12 year period and observe that overt and potential scams peaked in 2015 and 2018 respectively. We see that potential scams also increased during the COVID-19 pandemic. We use heuristics to pinpoint the types of cryptocurrencies most frequently used within scam advertisements. Bitcoin is most commonly found in potential scams while Ethereum appears more often than other cryptocurrencies in overt scams. We use machine learning classifiers to identify the scam actor types behind the posts categorised as overt and potential scams. We also classify the type of lure used by scammers. Our results indicate that the time principle is not a tactic used as frequently as expected. Finally, we observe the influence of the pandemic in the strategies used to lure victims, reflected in higher than expected use of the kindness principle in 2021 and 2022

Cryptocurrency scams: analysis and perspectives

Since the inception of Bitcoin in 2009, the market of cryptocurrencies has grown beyond the initial expectations, as witnessed by the thousands of tokenised assets available on the market, whose daily trades amount to dozens of USD billions. The pseudonymity features of these cryptocurrencies have attracted the attention of cybercriminals, who exploit them to carry out potentially untraceable scams. The wide range of cryptocurrency-based scams observed over the last ten years has fostered the research on the analysis of their effects, and the development of techniques to counter them. However, doing research in this field requires addressing several challenges: for instance, although a few data sources about cryptocurrency scams are publicly available, they often contain incomplete or misclassified data. Further, there is no standard taxonomy of scams, which leads to ambiguous and incoherent interpretations of their nature. Indeed, the unavailability of reliable datasets makes it difficult to train effective automatic classifiers that can detect and analyse cryptocurrency scams. In this paper, we perform an extensive review of the scientific literature on cryptocurrency scams, which we systematise according to a novel taxonomy. By collecting and homogenising data from different public sources, we build a uniform dataset of thousands of cryptocurrency scams.We devise an automatic tool that recognises scams and classifies them according to our taxonomy.We assess the effectiveness of our tool through standard performance metrics.We also give an in-depth analysis of the classification results, offering several insights into threat types, from their features to their connection with other types. Finally, we provide a set of guidelines that policymakers could follow to improve user protection against cryptocurrency scams

Identifying Crypto Addresses with Gambling Behaviors: A Graph Neural Network Approach

The development of blockchain technology has brought prosperity to the cryptocurrency market and has made the blockchain platform a hotbed of crimes. As one of the most rampant crimes, crypto gambling has more high risk of illegal activities due to the lack of regulation. As a result, identifying crypto addresses with gambling behaviors has emerged as a significant research topic. In this work, we propose a novel detection approach based on Graph Neural Networks named CGDetector, consisting of Graph Construction, Subgraph Extractor, Statistical Feature Extraction, and Gambling Address Classification. Extensive experiments of large-scale and heterogeneous Ethereum transaction data are implemented to demonstrate that our proposed approach outperforms state-of-the-art address classifiers of traditional machine learning methods. This work makes the first attempt to detect suspicious crypto gambling addresses via Graph Neural Networks by all EVM-compatible blockchain systems, providing new insights into the field of cryptocurrency crime detection and blockchain security regulation

Cryptocurrencies and future financial crime.

Background: Cryptocurrency fraud has become a growing global concern, with various governments reporting an increase in the frequency of and losses from cryptocurrency scams. Despite increasing fraudulent activity involving cryptocurrencies, research on the potential of cryptocurrencies for fraud has not been examined in a systematic study. This review examines the current state of knowledge about what kinds of cryptocurrency fraud currently exist, or are expected to exist in the future, and provides comprehensive definitions of the frauds identified. Methods: The study involved a scoping review of academic research and grey literature on cryptocurrency fraud and a 1.5-day expert consensus exercise. The review followed the PRISMA-ScR protocol, with eligibility criteria based on language, publication type, relevance to cryptocurrency fraud, and evidence provided. Researchers screened 391 academic records, 106 of which went on to the eligibility phase, and 63 of which were ultimately analysed. We screened 394 grey literature sources, 128 of which passed on to the eligibility phase, and 53 of which were included in our review. The expert consensus exercise was attended by high-profile participants from the private sector, government, and academia. It involved problem planning and analysis activities and discussion about the future of cryptocurrency crime. Results: The academic literature identified 29 different types of cryptocurrency fraud; the grey literature discussed 32 types, 14 of which were not identified in the academic literature (i.e., 47 unique types in total). Ponzi schemes and (synonymous) high yield investment programmes were most discussed across all literature. Participants in the expert consensus exercise ranked pump-and-dump schemes and ransomware as the most profitable and feasible threats, though pump-and-dumps were, notably, perceived as the least harmful type of fraud. Conclusions: The findings of this scoping review suggest cryptocurrency fraud research is rapidly developing in volume and breadth, though we remain at an early stage of thinking about future problems and scenarios involving cryptocurrencies. The findings of this work emphasise the need for better collaboration across sectors and consensus on definitions surrounding cryptocurrency fraud to address the problems identified

Investigating transactions in cryptocurrencies

This thesis presents techniques to investigate transactions in uncharted cryptocur- rencies and services. Cryptocurrencies are used to securely send payments on- line. Payments via the first cryptocurrency, Bitcoin, use pseudonymous addresses that have limited privacy and anonymity guarantees. Research has shown that this pseudonymity can be broken, allowing users to be tracked using clustering and tag- ging heuristics. Such tracking allows crimes to be investigated. If a user has coins stolen, investigators can track addresses to identify the destination of the coins. This, combined with an explosion in the popularity of blockchain, has led to a vast increase in new coins and services. These offer new features ranging from coins focused on increased anonymity to scams shrouded as smart contracts. In this study, we investigated the extent to which transaction privacy has improved and whether users can still be tracked in these new ecosystems. We began by analysing the privacy-focused coin Zcash, a Bitcoin-forked cryptocurrency, that is consid- ered to have strong anonymity properties due to its background in cryptographic research. We revealed that the user anonymity set can be considerably reduced using heuristics based on usage patterns. Next, we analysed cross-chain transac- tions collected from the exchange ShapeShift, revealing that users can be tracked as they move across different ledgers. Finally, we present a measurement study on the smart-contract pyramid scheme Forsage, a scam that cycled $267 million USD (of Ethereum) within its first year, showing that at least 88% of the participants in the scheme suffered a loss. The significance of this study is the revelation that users can be tracked in newer cryptocurrencies and services by using our new heuristics, which informs those conducting investigations and developing these technologies

Biztonság és jog: Konferenciakötet

Mindig is jelentős tudományos teher nehezedett azon kutatókra a társadalomtudományok terén, akik a „biztonság” – mint általános koncepció fogalmát - gazdasági, jogi, vagy iparági, szűk körben értelemezett szakmai szempontok alapján kívánták meghatározni. A jogtudományok területén a biztonság hiánya számos álláspont szerint egyfajta fenyegetést, veszélyt, kárt, hátrányt jelent, így maga a „biztonság” egy sajátos védelmi, konzervációs állapotot testesít meg. Így az értelmezés terén a joggyakorlatban gyakran alkalmazott ún. negatív megközelítés szolgálhat kiindulópontként tekintettel arra, hogy a biztonság fogalma legegyszerűbben annak hiányán keresztül értelmezhető. Figyelemmel a jogi értelemben vett biztonság multilaterális jellegére, ahogyan a gazdasági -, úgy szükségszerűen a jogi érdekek esetleges sérelme sem zárható ki teljes mértékben, tekintettel a fogalom relatív jellegére. Ugyanakkor az ember, mint jogalany biztonságát holisztikus megközelítéssel a személyét, valamint anyagi javait érő valamennyi fenyegetést és sérelmet figyelembe vevő, egymásra épülő megközelítés útján lehetséges értelmezni. A negyedik ipari forradalom következtében a fentiek alapján vett biztonság kérdésköre új dimenzót jelentve számottevő mértékben az online térben jelenik meg. Dinamikáját tekintve e kérdéskör - az információs-kommunikációs technológiák fejlődésével, különösen a jelenlegi COVID-19 okozta pandemiás helyzet kapcsán bekövetkezett változások okán – a korábbiakhoz képest jelentősen felgyorsult. A jelenlegi tudományos, műszaki és gazdasági fejlődés szintje, az ún. „state of art” új igényeket és jelenleg még nem ismert kockázatokat, kihívásokat generál. A konferencia 2020. december 8-án a fent részletezett aktualitásokra figyelemmel a Pécsi Tudományegyetem Állam-és Jogtudományi Kar Kriminológia és Büntetés-végrehajtási Jogi Tanszéke által került megszervezésre a biztonságpolitika területén folytatott kutatási munka hagyományának további ápolásaként. Az előadások anyagát jelen kötetünkben az Olvasó szíves figyelmébe ajánljuk.2020.12.0

Blockchain technology: Disruptor or enhancer to the accounting and auditing profession

The unique features of blockchain technology (BCT) - peer-to-peer network, distribution ledger, consensus decision-making, transparency, immutability, auditability, and cryptographic security - coupled with the success enjoyed by Bitcoin and other cryptocurrencies have encouraged many to assume that the technology would revolutionise virtually all aspects of business. A growing body of scholarship suggests that BCT would disrupt the accounting and auditing fields by changing accounting practices, disintermediating auditors, and eliminating financial fraud. BCT disrupts audits (Lombard et al.,2021), reduces the role of audit firms (Yermack 2017), undermines accountants' roles with software developers and miners (Fortin & Pimentel 2022); eliminates many management functions, transforms businesses (Tapscott & Tapscott, 2017), facilitates a triple-entry accounting system (Cai, 2021), and prevents fraudulent transactions (Dai, et al., 2017; Rakshit et al., 2022). Despite these speculations, scholars have acknowledged that the application of BCT in the accounting and assurance industry is underexplored and many existing studies are said to lack engagement with practitioners (Dai & Vasarhelyi, 2017; Lombardi et al., 2021; Schmitz & Leoni, 2019). This study empirically explored whether BCT disrupts or enhances accounting and auditing fields. It also explored the relevance of audit in a BCT environment and the effectiveness of the BCT mechanism for fraud prevention and detection. The study further examined which technical skillsets accountants and auditors require in a BCT environment, and explored the incentives, barriers, and unintended consequences of the adoption of BCT in the accounting and auditing professions. The current COVID-19 environment was also investigated in terms of whether the pandemic has improved BCT adoption or not. A qualitative exploratory study used semi-structured interviews to engage practitioners from blockchain start-ups, IT experts, financial analysts, accountants, auditors, academics, organisational leaders, consultants, and editors who understood the technology. With the aid of NVIVO qualitative analysis software, the views of 44 participants from 13 countries: New Zealand, Australia, United States, United Kingdom, Canada, Germany, Italy, Ireland, Hong Kong, India, Pakistan, United Arab Emirates, and South Africa were analysed. The Technological, Organisational, and Environmental (TOE) framework with consequences of innovation context was adopted for this study. This expanded TOE framework was used as the theoretical lens to understand the disruption of BCT and its adoption in the accounting and auditing fields. Four clear patterns emerged. First, BCT is an emerging tool that accountants and auditors use mainly to analyse financial records because technology cannot disintermediate auditors from the financial system. Second, the technology can detect anomalies but cannot prevent financial fraud. Third, BCT has not been adopted by any organisation for financial reporting and accounting purposes, and accountants and auditors do not require new skillsets or an understanding of the BCT programming language to be able to operate in a BCT domain. Fourth, the advent of COVID-19 has not substantially enhanced the adoption of BCT. Additionally, this study highlights the incentives, barriers, and unintended consequences of adopting BCT as financial technology (FinTech). These findings shed light on important questions about BCT disrupting and disintermediating auditors, the extent of adoption in the accounting industry, preventing fraud and anomalies, and underscores the notion that blockchain, as an emerging technology, currently does not appear to be substantially disrupting the accounting and auditing profession. This study makes methodological, theoretical, and practical contributions. At the methodological level, the study adopted the social constructivist-interpretivism paradigm with an exploratory qualitative method to engage and understand BCT as a disruptive innovation in the accounting industry. The engagement with practitioners from diverse fields, professions, and different countries provides a distinctive and innovative contribution to methodological and practical knowledge. At the theoretical level, the findings contribute to the literature by offering an integrated conceptual TOE framework. The framework offers a reference for practitioners, academics and policymakers seeking to appraise comprehensive factors influencing BCT adoption and its likely unintended consequences. The findings suggest that, at present, no organisations are using BCT for financial reporting and accounting systems. This study contributes to practice by highlighting the differences between initial expectations and practical applications of what BCT can do in the accounting and auditing fields. The study could not find any empirical evidence that BCT will disrupt audits, eliminate the roles of auditors in a financial system, and prevent and detect financial fraud. Also, there was no significant evidence that accountants and auditors required higher-level skillsets and an understanding of BCT programming language to be able to use the technology. Future research should consider the implications of an external audit firm as a node in a BCT network on the internal audit functions. It is equally important to critically examine the relevance of including programming languages or codes in the curriculum of undergraduate accounting students. Future research could also empirically evaluate if a BCT enabled triple-entry system could prevent financial statements and management fraud

Blockchain Technology: Disruptor or Enhnancer to the Accounting and Auditing Profession

The unique features of blockchain technology (BCT) - peer-to-peer network, distribution ledger, consensus decision-making, transparency, immutability, auditability, and cryptographic security - coupled with the success enjoyed by Bitcoin and other cryptocurrencies have encouraged many to assume that the technology would revolutionise virtually all aspects of business. A growing body of scholarship suggests that BCT would disrupt the accounting and auditing fields by changing accounting practices, disintermediating auditors, and eliminating financial fraud. BCT disrupts audits (Lombard et al.,2021), reduces the role of audit firms (Yermack 2017), undermines accountants' roles with software developers and miners (Fortin & Pimentel 2022); eliminates many management functions, transforms businesses (Tapscott & Tapscott, 2017), facilitates a triple-entry accounting system (Cai, 2021), and prevents fraudulent transactions (Dai, et al., 2017; Rakshit et al., 2022). Despite these speculations, scholars have acknowledged that the application of BCT in the accounting and assurance industry is underexplored and many existing studies are said to lack engagement with practitioners (Dai & Vasarhelyi, 2017; Lombardi et al., 2021; Schmitz & Leoni, 2019). This study empirically explored whether BCT disrupts or enhances accounting and auditing fields. It also explored the relevance of audit in a BCT environment and the effectiveness of the BCT mechanism for fraud prevention and detection. The study further examined which technical skillsets accountants and auditors require in a BCT environment, and explored the incentives, barriers, and unintended consequences of the adoption of BCT in the accounting and auditing professions. The current COVID-19 environment was also investigated in terms of whether the pandemic has improved BCT adoption or not. A qualitative exploratory study used semi-structured interviews to engage practitioners from blockchain start-ups, IT experts, financial analysts, accountants, auditors, academics, organisational leaders, consultants, and editors who understood the technology. With the aid of NVIVO qualitative analysis software, the views of 44 participants from 13 countries: New Zealand, Australia, United States, United Kingdom, Canada, Germany, Italy, Ireland, Hong Kong, India, Pakistan, United Arab Emirates, and South Africa were analysed. The Technological, Organisational, and Environmental (TOE) framework with consequences of innovation context was adopted for this study. This expanded TOE framework was used as the theoretical lens to understand the disruption of BCT and its adoption in the accounting and auditing fields. Four clear patterns emerged. First, BCT is an emerging tool that accountants and auditors use mainly to analyse financial records because technology cannot disintermediate auditors from the financial system. Second, the technology can detect anomalies but cannot prevent financial fraud. Third, BCT has not been adopted by any organisation for financial reporting and accounting purposes, and accountants and auditors do not require new skillsets or an understanding of the BCT programming language to be able to operate in a BCT domain. Fourth, the advent of COVID-19 has not substantially enhanced the adoption of BCT. Additionally, this study highlights the incentives, barriers, and unintended consequences of adopting BCT as financial technology (FinTech). These findings shed light on important questions about BCT disrupting and disintermediating auditors, the extent of adoption in the accounting industry, preventing fraud and anomalies, and underscores the notion that blockchain, as an emerging technology, currently does not appear to be substantially disrupting the accounting and auditing profession. This study makes methodological, theoretical, and practical contributions. At the methodological level, the study adopted the social constructivist-interpretivism paradigm with an exploratory qualitative method to engage and understand BCT as a disruptive innovation in the accounting industry. The engagement with practitioners from diverse fields, professions, and different countries provides a distinctive and innovative contribution to methodological and practical knowledge. At the theoretical level, the findings contribute to the literature by offering an integrated conceptual TOE framework. The framework offers a reference for practitioners, academics and policymakers seeking to appraise comprehensive factors influencing BCT adoption and its likely unintended consequences. The findings suggest that, at present, no organisations are using BCT for financial reporting and accounting systems. This study contributes to practice by highlighting the differences between initial expectations and practical applications of what BCT can do in the accounting and auditing fields. The study could not find any empirical evidence that BCT will disrupt audits, eliminate the roles of auditors in a financial system, and prevent and detect financial fraud. Also, there was no significant evidence that accountants and auditors required higher-level skillsets and an understanding of BCT programming language to be able to use the technology. Future research should consider the implications of an external audit firm as a node in a BCT network on the internal audit functions. It is equally important to critically examine the relevance of including programming languages or codes in the curriculum of undergraduate accounting students. Future research could also empirically evaluate if a BCT-enabled triple-entry system could prevent financial statements and management fraud